Thinking is Power

Are Electromagnetic Fields
Making me Ill?
by Brad Roth.

Recently I stumbled on a YouTube video about critical thinking in education, featuring Melanie Trecek-King (of the website “Thinking is Power”), Bertha Vazquez (with the Center for Inquiry) and Daniel Reed (the West Virginia Skeptics Society). I wasn’t expecting much, but as I listened I became enthralled. I highly recommend you spend some time exploring Thinking is Power, and perhaps follow it on Facebook. Trecek-King’s mantra is “Teach Skills Not Facts,” and she is trying to teach the skills of critical thinking. As I listened, I began to ask myself if I am doing all I can to teach critical thinking? In particular, are critical thinking skills emphasized in Intermediate Physics for Medicine and Biology, and in my popular science book Are Electromagnetic Fields Making Me Ill? I decided to use Are Electromagnetic Fields Making Me Ill? as a test case.

One of the key ideas in my book is the clinical trial. Critical thinking lies at the heart of such trials. In the chapter about the health effects of magnets, I discuss the importance of clinical trials being double blind, randomized, and placebo controlled. Why are these features crucial? They keep you from fooling yourself. In particular, a study being double blind (meaning that “not only the patient, but also the physician, does not know who is in the placebo or treatment group”) is vital to prevent a doctor from inadvertently signalling to the patient which group they are in. One of Trecek-King’s favorite sayings is the quote by Richard Feynman that “you must not fool yourself—and you are the easiest person to fool.” That sums up why double blinding is so important.

Placebos are discussed several times in my book. My favorite example of a placebo comes from a clinical trial to evaluate a new drug. “If a medication is being tested, the placebo is a sugar pill with the same size, shape, color, and taste as that of the drug.” One reason I dwell on placebos is that sometimes they are difficult to design. When testing if permanent magnets can reduce pain, “this means that some patients received treatment with real magnets, and others were treated with objects that resembled magnets but produced a much weaker magnetic field or no magnetic field at all.” It is hard to make a “fake magnet” or a “mock transcranial direct current stimulator.” Yet, designing the placebo is exactly a situation where critical thinking skills are essential.

Critical thinking overlaps with the scientific method, with its emphasis on examining the evidence. In Are Electromagnetic Fields Making Me Ill?, my goal was to present the evidence and then let the reader decide what to believe. But that’s hard. For instance, the experimental laboratory studies about the biological effects of cell phone radiation are a mixed bag. Some studies see effects, and some don’t. You can argue either way depending on what studies you emphasize. I tried to rely on critical reviews to sort all this out (after all, where better to find critical thinking than in a critical review). But even the critical reviews are not unanimous. I probably should’ve examined each article individually and weighed its pros and cons, but that would have taken years (the literature on this topic is vast).

Trecek-King often discusses the importance of finding reliable sources of information. I agree, but this too is not always easy. For instance, what could be more authoritative than a report produced by the National Academy of Sciences? In Are Electromagnetic Fields Making Me Ill? I laud the Stevens report published in the 1990s about the health hazards (or should I say lack of hazards) from powerline magnetic fields. Yet, I’m skeptical about the National Academies report published in 2020 regarding microwave weapons being responsible for the Havana Syndrome. What do I conclude? Sometimes deferring to authority is useful, but not always. You can’t delegate critical thinking.

I have found that one useful tool for teaching and illustrating critical thinking are the Point/Counterpoint articles published in the journal Medical Physics. In Are Electromagnetic Fields Making Me Ill? I cite three such articles, on magnets reducing pain, on cell phone radiation causing cancer, and on the safety of airport backscatter radiation scanners. Each of these articles are in the form of a debate, and any lack of critical thinking will be exposed and debunked in the rebuttals. I wrote

When I taught medical physics to college students, we spent 20 minutes each Friday afternoon discussing a point/counterpoint article. One feature of these articles that makes them such an outstanding teaching tool is that there exists no right answer, only weak or strong arguments. Science does not proceed by proclaiming universal truths, but by accumulating evidence that allows us to be more or less confident in our hypotheses. Conclusions beginning with “the evidence suggests…” are the best science has to offer.

One skill I emphasized in my teaching using IPMB, but which I don’t see mentioned by Trecek-King, is estimation. For instance, when discussing the potential health benefits or hazards of static magnetic fields, I calculated the energy of an electron in a magnetic field and compared it to its thermal energy. Such a simple order-of-magnitude estimate shows that thermal energy is vastly greater than magnetic energy, implying that static magnetic fields should have no effect on chemical reactions. Similarly, in my chapter about powerline magnetic fields, I estimated the electric field induced in the body by a 60 Hz magnetic field and compare it to endogenous electric fields due mainly to the heart’s electrical activity. Finally, in my discussion about cell phone radiation I compared the energy of a single radio-frequency photon to the energy of a chemical bond to prove that cell phones cannot cause cancer by directly disrupting DNA. This ability to estimate is crucial, and I believe it should be included under the umbrella of critical thinking skills.

In the video I watched, Trecek-King discussed the idea of consensus, and the different use of this term among scientists and nonscientists. When I analyzed transcranial direct current stimulation, I bemoaned the difficulty in finding a consensus among different research groups.

Finding the truth does not come from a eureka moment, but instead from a slow slog ultimately leading to a consensus among scientists.

I probably get closest to what scientists mean by consensus at the close of my chapter on the relationship (actually, the lack of relationship) between 5G cell phone radiation and COVID-19:

Scientific consensus arises when a diverse group of scientists openly scrutinizes claims and critically evaluates evidence.

Consensus is only valuable if it arises from individuals independently examining a body of evidence, debating an issue with others, and coming to their own conclusion. Peer review, so important in science, is one way scientists thrash out a consensus. I wrote

The reason for peer review is to force scientists to convince other scientists that their ideas and data are sound.

Perhaps the biggest issue in critical thinking is bias. One difficulty is that bias comes in many forms. One example is publication bias: “the tendency for only positive results to be published.” Another is recall bias that can infect a case-control epidemiological study. But the really thorny type of bias arises from prior beliefs that scientists may be reluctant to abandon. In Are Electromagnetic Fields Making Me Ill? I tell the story of how Robert Tucker and Otto Schmidt performed an experiment to determine if people could detect 60 Hz magnetic fields. They spent five years examining their experiment for possible systematic errors, and eventually concluded that 60 Hz fields are not detectable. I wrote “One reason the bioelectric literature is filled with inconsistent results may be that not all experimenters are as diligent as Robert Tucker and Otto Schmitt.”

After listening to Trecek-King’s video, I began to wonder if the Tucker and Schmidt experiment might alternatively be viewed be a cautionary tale about bias. Was their long effort a heroic example of detecting and eliminating systematic error, or was it a bias marathon where they slaved away until they finally came to the conclusion they wanted? I side with the heroic interpretation, but it does make me wonder about the connection between bias and experimental design. The hallmark of a good experimental scientist is the ability to identify and remove systematic errors from an experiment. Yet one must be careful to root out all systematic errors, not just those that affect the results in one direction. The conclusion: science is difficult, and you must be constantly on guard about fooling yourself.

I reexamined Are Electromagnetic Fields Making Me Ill? to search for signs of my own biases, and came away a little worried. For instance, when talking about 5G cell phone radiation risks, I wrote

The 5G cell phone debate strikes me as déjà vu. First Mesmer’s “animal magnetism” treatments ascended in popularity and then declined. Next the use of magnets for therapy rose and fell. Then came the power line debate; a crescendo followed by a diminuendo. Later the dispute over traditional cell phones came and went. Now, we are doing it all over again for 5G.

After listening to Trecek-King’s video, I am nervous that this was an inadvertent confession of bias. Do my past experiences predispose me to reject claims about electromagnetic fields being dangerous? Or am I merely stating a hard-earned opinion based on experience? Or are those the same thing? Is it bias to believe that Lucy will pull that football away from Charlie Brown at the last second?

I tried to focus my book on the evidence and not on personal opinions, but can we ever be sure? If I was a proponent of the idea that cell phones cause cancer, I might point to the above déjà vu quote as evidence that the author of Are Electromagnetic Fields Making Me Ill? was biased. Yet, if you asked me now if I still believed what I wrote in that quote, I would say “you betcha I do.” Does my statement have relevance to the 5G cell phone debate? I think it does, although it’s no substitute for hard evidence. Can we ever truly free ourselves from our biases? Perhaps not, but at least we can be aware of them, so as to be on guard.

All this discussion about critical thinking and bias is related to the claims of pseudoscience and alternative medicine. At the end of Are Electromagnetic Fields Making Me Ill? I ponder the difficulty of debunking false claims.

The study of biological effects of weak electric and magnetic fields attracts pseudoscientists and cranks. Sometimes I have a difficult time separating the charlatans from the mavericks. The mavericks—those holding nonconformist views based on evidence (sometimes a cherry-picked selection of the evidence)—can be useful to science, even if they are wrong. The charlatans—those snake-oil salesmen out to make a quick buck—either fool themselves or fool others into believing silly ideas or conspiracy theories. We should treat the mavericks with respect and let peer review correct their errors. We should treat the charlatans with disdain. I wish for the wisdom to tell them apart.

I’ll give Trecek-King’s the last word. Another of her mantras, which to me sums up why we care about critical thinking, is:

I am not saying that all of our problems can be solved with critical thinking. I’m saying that it is our best chance.

Critical Thinking in Education, featuring Melanie Trecek-King, Bertha Vazquez, and Daniel Reed

https://www.youtube.com/watch?v=QkPtC3gn6JE

Lucy, Charlie Brown, and the football.

https://www.youtube.com/watch?v=mC5MzvgE4c0

And another.

https://www.youtube.com/watch?v=ddmXM-96-no

 A Life Preserver for Staying Afloat in a Sea of Misinformation.

https://www.youtube.com/watch?v=JkGsxtbetts

Good Vibrations

In Chapter 10 of Intermediate Physics for Medicine and Biology, Russ Hobbie and I discuss negative feedback loops. Feedback is often used to maintain an important variable nearly constant. This idea underlies homeostasis and is fundamental to physiology.

"Are Physiological Oscillations Physiological?"
by Ivy Xiong and Alan Garfinkel.

So imagine my surprise when I read Ivy Xiong and Alan Garfinkel’s topical review in The Journal of Physiology titled “Are Physiological Oscillations Physiological?” (In Press), which changed the way I look at homeostasis and feedback. Its abstract states

Despite widespread and striking examples of physiological oscillations, their functional role is often unclear. Even glycolysis, the paradigm example of oscillatory biochemistry, has seen questions about its oscillatory function. Here, we take a systems approach to argue that oscillations play critical physiological roles, such as enabling systems to avoid desensitization, to avoid chronically high and therefore toxic levels of chemicals, and to become more resistant to noise. Oscillation also enables complex physiological systems to reconcile incompatible conditions such as oxidation and reduction, by cycling between them, and to synchronize the oscillations of many small units into one large effect. In pancreatic β-cells, glycolytic oscillations synchronize with calcium and mitochondrial oscillations to drive pulsatile insulin release, critical for liver regulation of glucose. In addition, oscillation can keep biological time, essential for embryonic development in promoting cell diversity and pattern formation. The functional importance of oscillatory processes requires a re-thinking of the traditional doctrine of homeostasis, holding that physiological quantities are maintained at constant equilibrium values, a view that has largely failed in the clinic. A more dynamic approach will initiate a paradigm shift in our view of health and disease. A deeper look into the mechanisms that create, sustain and abolish oscillatory processes requires the language of nonlinear dynamics, well beyond the linearization techniques of equilibrium control theory. Nonlinear dynamics enables us to identify oscillatory (‘pacemaking’) mechanisms at the cellular, tissue and system levels.

In their introduction, Xiong and Garfinkel get straight to the point. Homeostasis examines an equilibrium stabilized by negative feedback loops. Such systems are studied by linearizing the system around the equilibrium point. Oscillatory systems, on the other hand, correspond to limit cycle attractors in a nonlinear system. The regulatory mechanism must both create the oscillation and stabilize it.

In Russ’s and my defense, we do talk about oscillations in our chapter on feedback. One source of oscillations is when a feedback loop has two time constants (Section 10.6), but these aren’t what Xiong and Garfinkel are talking about because those oscillations are transient and only affect the approach to equilibrium. A true oscillation is more like the case of negative feedback plus a time delay (Sec. 10.10 of IPMB). Russ and I mention that such a model can lead to sustained oscillations, but in light of Xiong and Garfinkel’s review I wish now we had stressed that observation more. We analyzed the specific case but missed the big picture; the paradigm shift.

Another mechanism Xiong and Garfinkel highlight is what they call “negative resistance.” They use the FitzHugh-Nagumo model (analyzed in Problem 35 of Chapter 10 in IPMB) as an example of “short-range destabilizing positive feedback, making the equilibrium point inherently unstable.” Although they don’t mention it, I think another example is the Hodgkin and Huxley model of the squid axon with an added constant leakage current destabilizing the resting potential (Section 6.18 of IPMB). Xiong and Garfinkel do discuss oscillations in the heart’s sinoatrial node, which operate by a mechanism similar to the Hodgkin-Huxley model with that extra current.

A third mechanism generating oscillations is illustrated by premature ventricular contractions in the heart caused by “the repolarization gradient that manifests as the T wave.” As a cardiac modeling guy, I am embarrassed that I’m not more aware of this fascinating idea. To learn about it, I recommend you (and I) start with Xiong and Garfinkel’s review (we have no excuse; it’s open access) and then examine some of their references.

Even more interesting is Xiong and Garfinkel’s contention that “oscillations are not an unwanted product of negative feedback regulation. Rather, they represent an essential design feature of nearly all physiological systems.” They’re a feature, not a bug. Presumably evolution has selected for oscillating systems. I wonder how. (Xiong already has a background in molecular biology, bioinformatics, and mathematical modeling; perhaps while she’s at it she should add evolutionary biology.) Let me stress that Xiong and Garfinkel are not merely speculating; they provide many examples and cite many publications supporting this hypothesis.

A key paragraph in their paper introduces a new term: “homeodynamics.”

“If oscillatory processes are central to physiology, then we will need to take a fresh look at the doctrine of homeostasis. We suggest that the concept of homeostasis needs to be parsed into two separate components. The first component is the idea that physiological processes are regulated and must respond to environmental changes. This is obviously critical and true. The second component is that this physiological regulation takes the form of control to a static equilibrium point, a view which we believe is largely mistaken. ‘Homeodynamics’ is a term that has been used in the past to try to combine regulation with the idea that physiological processes are oscillatory... It may be time to revive this terminology.”

This topical review reminds me of Leon Glass and Michael Mackey’s wonderful book From Clocks to Chaos (cited in IPMB), which introduced the idea of a “dynamical disease.” Like Glass and Mackey, Xiong and Garfinkel present a convincing argument in support of a new paradigm in biology, rooted in the mathematics of nonlinear dynamics. 

In their cleverly titled section on “Bad Vibrations,” Xiong and Garfinkel note that “not all oscillations serve a positive physiological function. Oscillations in physiology can also be pathological and dysfunctional.” I suspect their section title is a sly reference to the Beach Boys hit “Good Vibrations.” After all, Xiong and Garfinkel are both from California and their review can be summed up as the mathematical modeling of good vibrations.

From Clocks to Chaos,
by Glass and Mackey.

You know what: I think the upcoming 6^th edition of Intermediate Physics for Medicine and Biology needs more emphasis on nonlinear dynamics. I’m lucky Xiong and Garfinkel’s article came out just as Gene Surdutovich and I were revising and updating the 5^th edition of IPMB. God Only Knows that as I sit here In My Room working on the revision I’ll have Fun, Fun, Fun. Don’t Worry Baby, now that it’s spring and we have The Warmth of the Sun, Gene and I should make good progress. Unfortunately, because we’re working here in Michigan, we can’t occasionally take a break to Catch A Wave. Wouldn’t It be Nice if we could go on a Surfin’ Safari? (Sorry, I got a little carried away.)

So the answer to the question in the title—are physiological oscillations physiological?—is a resounding “Yes!” I’ll conclude with Xiong and Garfinkel’s final sentence, which I wholeheartedly agree with (except for the annoying British spelling of “center”):

It is time to bring this conception of physiological oscillations to the centre of biological discourse.

“Good Vibrations” by the Beach Boys.

https://www.youtube.com/watch?v=apBWI6xrbLY

 

 Ivy Xiong discussing mathematical modeling of biological oscillations.

https://www.youtube.com/watch?v=AUmpgrDpT08&list=PLreJ534rlE5XZdRbtftkW9gD1u6w-jTZt&index=6&t=44s

Authors at Oakland: A Celebration of the Book

Are Electromagnetic Fields Making Me Ill?,
by Brad Roth

Every year the Kresge Library at Oakland University hosts an event called “Authors at Oakland” where they honor publications by Oakland University faculty. This year was “a celebration of the book.” Intermediate Physics for Medicine and Biology was featured at a previous Authors at Oakland event, and this year I submitted Are Electromagnetic Fields Making Me Ill? Two authors were selected to give a short talk about their book, and I was one of them. So on Wednesday, March 20 I spoke to an audience of OU librarians, members of the faculty senate library committee, and other interested professors and students.

The talk was not recorded but below is a transcript, as best as I can remember it.

Thank you for selecting my book Are Electromagnetic Fields Making Me Ill? to be featured here at Authors at Oakland. My friend David Garfinkle once told me that any time a book has a title in the form of a question, the answer’s always “no.” That’s true for my book, and sums it up in a nutshell.

How did I come to write this book? In November of 2019, just before Covid arrived, I was asked to participate in a town hall meeting in Rochester, Michigan about the then-new 5G cell phones. I was to be the health effects expert. I thought I was going to give a short talk to a quiet and respectful audience. Little did I know what was in store. [At this point I showed about the first one and a half minutes of the video below.]

I discussed the hazards of 5G cell phone radiation at a town hall meeting in Rochester, Michigan in 2019. The audience was not convinced by my claim that the risks are small. https://www.youtube.com/watch?v=smQ0Nnz7lLk

This experience got me to wondering why people believe things that aren’t supported by the evidence and what could I do about it? In response to the second question, I wrote this book.

The book covers several topics, but today I’ll focus on the issue that started it all: cell phones and cancer.

Not everyone agrees with me that 5G cell phone radiation is harmless. Devra Davis has written a book titled Disconnect, in which she claims to tell “the TRUTH about cell phone RADIATION, what the INDUSTRY has done to HIDE it, and how to PROTECT your FAMILY.” I disagree with her conclusions, but the issue shouldn’t be viewed as my word against hers. Let’s look at the evidence. That’s how science works.

The electromagnetic spectrum.
(From: https://www.niehs.nih.gov/health/topics/agents/
emf/index.cfm)

To start we need to discuss a little physics. Electromagnetic waves come in many frequencies, from extremely low frequencies like those produced by 60 Hz power lines, to intermediate frequencies such as from cell phones, to very high frequencies such as x-rays.

Quantum mechanics tells us that electromagnetic radiation is not continuous but comes in lumps called photons. The energy of a photon is proportional to its frequency. Very high frequency photons like for x-rays have enough energy that they can disrupt DNA, causing mutations leading to cancer. However, cell phones operate at a much lower frequency, on the order of a gigahertz (one billion oscillations per second), in the realm of microwaves. These photons have an energy of about 0.000004 eV (an eV or “electron volt” is a unit of energy appropriate when discussing single atoms or molecules). What should we compare that energy to? All molecules are bouncing around randomly, called thermal motion. The thermal energy at our body temperature is about 0.02 eV. A cell phone photon would be swamped by the thermal noise. Chemical bonds have strengths of several electron volts. A cell phone photon is far too weak to break bonds, so they can’t directly disrupt DNA and cause cancer like x-ray photons can. If they have any effect it must be an indirect one, such as affecting our immune system or suppressing our body’s ability to repair DNA damage.

A microwave oven.
(Consumer Reports, CC BY-SA 4.0,
https://creativecommons.org/
licenses/by-sa/4.0, via Wikimedia Commons)

Even though one photon can’t damage our tissue, you might be wondering what would happen if we deposited many, many photons into our body? Physicists have a word for that: “heat.” We know microwaves can heat tissue. You prove that every time you warm up your leftovers in your microwave oven. However, physicists understand how microwaves heat tissue very well, and can predict how hot tissue will get when exposed to microwaves. Cell phones don’t emit enough microwave radiation to significantly heat tissue. The Federal Communications Commission limits the amount of radiation a cell phone can emit to levels that don’t cause significant heating. Your cell phone doesn’t cook your brain. If microwave radiation represents a hazard to our tissue, it’s not only through an indirect effect but also a nonthermal effect.

Let’s now look at four types of evidence about the risk of cell phone radiation: 1) theoretical analysis, 2) cancer rates, 3) epidemiological evidence, and 4) laboratory experiments.

Asher Sheppard and his colleagues have analyzed every theoretical mechanism they could think of to determine if microwaves have a significant affect on our tissue. After an exhaustive search, they concluded that

In the frequency range from several megahertz to a few hundred gigahertz, the focus of this paper, the principal mechanism for biological effects, and the only well-established mechanism, is the heating of tissues.

I can imagine that you’re thinking “well, maybe those armchair theorists just weren’t smart enough to dream up the correct mechanism.” Perhaps, but the point I want to make is that the concern about cell phone radiation isn’t being driven by a theoretical prediction. Theory does not predict there should be an effect.

Cell phone use and brain cancer trends between 1976 and 2006.
(Data from Inskip et al.)

Now look at this plot of brain cancer trends. Back in the 1980s, when I was a graduate student, no one had cell phones. The use of cell phones has exploded since then. The data shown only goes out to about 2010, but if you extend the data to today essentially everyone has a cell phone. However, the cancer rate has been flat over those decades. And the brain cancer rate, in particular, has been nearly flat. If cell phones are causing brain cancer, it’s not a strong enough signal to show up in the cancer rate data.

Epidemiology studies examine large groups of people, some exposed to a hazard and some not, to compare their health. One of the first epidemiological studies is called the INTERPHONE study, and it did suggest a weak association of heavy cell phone use with cancer. INTERPHONE was a case control study; the researchers interviewed many people with brain cancer to determine their prior cell phone use, and compared these people to a control group without cancer. These studies are useful for getting data on rare hazards quickly, but they’re susceptible to biases, such as “recall bias” where a person with cancer who used their cell phone a lot will remember that clearly and perhaps regretfully while a member of the control group might not remember whether or not they even used a cell phone at all. A cohort study is a better type of epidemiological analysis. A large number of people, some cell phone users and some not, are followed for many years to see who gets cancer. Two large cohort studies—the Million Women Study in Europe and another study that involved essentially the entire population of Denmark—didn’t indicate a signal for an increased rate of cancer caused by cell phone use. A meta-analysis of many epidemiological studies by Martin Röösli and his coworkers concluded that

Epidemiological studies do not suggest increased brain or salivary gland tumor risk with [mobile phone] use, although some uncertainty remains regarding long latency periods (>15 years), rare brain tumor subtypes, and [mobile phone] usage during childhood.

Another large cohort study, called COSMOS, is now being carried out in Europe. When I was preparing this Powerpoint presentation, I thought I’d have to tell you that we’ll need to wait a few years until the results are published. Then, just this week, a preliminary report found that there’s no evidence that cell phone use is associated with higher rates of brain cancer. Some people might claim that there’s a long latency period between the exposure to cell phone radiation and the occurrence of cancer, and that a large uptick in the cancer rate will happen soon. Maybe, but as each year goes by that scenario becomes less and less likely.

The final type of evidence is laboratory experiments, such as studies using rats, mice, or cells in a dish. The evidence here is mixed; many experiments see effects and many do not. In fact, you could make a compelling case for or against cell phone health effects, depending on which articles you read. Unfortunately, the quality of these studies is also mixed.

Often scientists sometimes conduct a systematic review, weighing the pros and cons of the many experiments. For example, Anne Perrin and her collaborators reviewed the effects of radiofrequency electromagnetic fields on the blood brain barrier, and found that

recent studies provide no convincing proof of deleterious effects of [radiofrequency radiation] on the integrity of the [blood brain barrier].

But other systematic reviews have come to different conclusions, and I fear it’s difficult to draw definite conclusions from the experimental investigations.

Federal agencies—such as the Food and Drug Administration, the Center for Disease Control, and the National Cancer Institute (part of the National Institutes of Health)—often conduct their own reviews of the evidence. My favorite is the National Cancer Institute, which was the agency that got the round of boos during that 5G town hall meeting I participated in. These aren’t bureaucrats conducting the review, but instead are our nation’s top cancer scientists. They concluded that

The human body does absorb energy from devices that emit radiofrequency radiation. The only consistently recognized biological effect of radiofrequency radiation absorption in humans that the general public might encounter is heating to the area of the body where a cell phone is held (e.g., the ear and head). However, that heating is not sufficient to measurably increase core body temperature. There are no other clearly established dangerous health effects on the human body from radiofrequency radiation.

So, the evidence from theoretical analysis, cancer trends, epidemiology, and experiments makes a strong case that there are no health risks from cell phone radiation. Impossibility proofs are difficult in biology and medicine, but to me the evidence is compelling that the electromagnetic waves emitted by cell phones are safe.

A final question is if we should believe the scientists. Should we trust the National Cancer Institute to provide a unbiased review, or are they trying to hide hazardous effects. I believe a conspiracy secretly carried out by hundreds if not thousands of scientists and medical doctors is absurd. In my book I wrote

Dangers arising from cell phone radiation strike me as unlikely, but not inconceivable. However, the claims that there exists a vast plot, with scientists colluding to conceal the facts, are ridiculous.

My book covers other topics besides just cell phone radiation. There’s a chapter on power line electric and magnetic fields causing leukemia, another on the Havana Syndrome, and others. My conclusion is that all these potential affects of electromagnetic fields are overblown.

Finally, in the acknowledgments section of my book I thank the Kresge Library for “assisting me with obtaining books and articles related to this research.” In particular, the interlibrary loan office here at Kresge Library has been essential to my research. I worked them pretty hard. You can’t write a book like this without a good interlibrary loan department.

Thank you. Does anyone have questions?

I must admit the biggest applause arose from my comment about the interlibrary loan office, but then the crowd was largely librarians. Overall Authors at Oakland was a wonderful event, and I deeply appreciate being invited to speak at it.

Oh, Myyy!

Recently I was reading an article by Ramsay Lewis and Yuhong Dong in The Epoch Times titled Invisible Electromagnetic Fields: Do They Harm Your Health? My friend and colleague David Garfinkle once told me that whenever you see a book or article whose title is in the form of a question, the answer is always “no.” I assumed that would be the case for this article, and I began reading.

The article describes how citizens of Virginia Beach opposed an offshore renewable energy project, justifying their opposition in part because of possible health hazards from electric and magnetic fields produced by transmission cables.

The article started off well and discussed many of the issues described in Chapter 9 of Intermediate Physics for Medicine and Biology and in my book Are Electromagnetic Fields Making Me Ill? (which, by the way, does follow Garfinkle’s rule of the title question having “no” for an answer). Then, suddenly, Lewis and Dong took a bizarre turn. They wrote

In repeated experiments, Nobel Prize laureate Professor Luc Montagnier amazingly demonstrated that a low intensity electromagnetic field (EMF) of 7 HZ (similar to Schumann resonances), could produce DNA in a tube of pure water, simply by being adjacent to another tube containing DNA. In other words, he created something—DNA—out of nothing, simply by being close to DNA and adding low frequency EMFs.

Wait... What?! This sounded serious enough that I decided to look into it. After all, the idea was championed by one of the discovers of HIV, the virus responsible for AIDS.

Luc Montagnier in 2008
Prolineserver, GFDL 1.2, via Wikimedia Commons

I found a paper published by Montagnier and his coworkers (Montagnier et al., 2009, “Electromagnetic signals are produced by aqueous nanostructures derived from bacterial DNA sequences,” Interdisciplinary Sciences: Computational Life Sciences, Volume 1, Pages 81–90). Below I reproduce their abstract.

A novel property of DNA is described: the capacity of some bacterial DNA sequences to induce electromagnetic waves at high aqueous dilutions. It appears to be a resonance phenomenon triggered by the ambient electromagnetic background of very low frequency waves. The genomic DNA of most pathogenic bacteria contains sequences which are able to generate such signals. This opens the way to the development of highly sensitive detection system for chronic bacterial infections in human and animal diseases.

The key phrase in the abstract is “at high aqueous dilutions.” The authors repeatedly made 10:1 dilutions of the DNA solution. After 18 dilutions, the concentration of DNA should be 0.000000000000000001 times what it was originally. The purported electromagnetic wave effect persisted, even though there was no DNA left in the sample. The water “remembered” the DNA. It’s homeopathy all over again.

Oh, Myyy! This is the worst sort of pseudoscience.

A 2010 interview in Science politely hinted that this idea is absurd.

Virologist and Nobel laureate Luc Montagnier announced earlier this month that, at age 78, he will take on the leadership of a new research institute at Jiaotong University in Shanghai. What has shocked many scientists, however, isn’t Montagnier’s departure from France but what he plans to study in China: electromagnetic waves that Montagnier says emanate from the highly diluted DNA of various pathogens…

But Montagnier’s new direction evokes one of the most notorious affairs in French science: the “water memory” study by immunologist Jacques Benveniste. Benveniste, who died in 2004, claimed in a 1988 Nature paper that IgE antibodies have an effect on a certain cell type even after being diluted by a factor of 10¹²⁰. His claim was interpreted by many as evidence for homeopathy, which uses extreme dilutions that most scientists say can’t possibly have a biological effect. After a weeklong investigation at Benveniste’s lab, Nature called the paper a “delusion.”

Here’s part of the interview with Montagnier.

Q: You have called Benveniste a modern Galileo. Why? 

L.M.: Benveniste was rejected by everybody, because he was too far ahead. He lost everything, his lab, his money. … I think he was mostly right, but the problem was that his results weren’t 100% reproducible. 

Q: Do you think there’s something to homeopathy as well? 

L.M.: I can’t say that homeopathy is right in everything. What I can say now is that the high dilutions are right. High dilutions of something are not nothing. They are water structures which mimic the original molecules. We find that with DNA, we cannot work at the extremely high dilutions used in homeopathy; we cannot go further than a 10⁻¹⁸ dilution, or we lose the signal. But even at 10⁻¹⁸, you can calculate that there is not a single molecule of DNA left. And yet we detect a signal.

Why should we care about all this silliness? Wouldn’t it be better to just ignore it? Here’s the problem: Climate change is real. There’s a consensus among scientists that it’s a serious, man-made crisis that must be addressed. One way to fight climate change it is to build alternative sources of energy, such as offshore wind farms. Yet citizens and journalists are citing ridiculous nonsense like Montagnier’s water memory hypothesis to oppose wind farms. Quackery and voodoo science are being used to impede solutions to what may be the most dire challenge mankind has ever faced.

To quote Charles Dickens, “I’ll retire to bedlam.”

Co-discoverer of HIV Luc Montagnier dies aged 89. BBC News

https://www.youtube.com/watch?v=Iat2FncJ1to

 

What is Homeopathy, by Science Saves.

https://www.youtube.com/watch?v=Rw766-Z97BI

 

Bill Catterall (1946–2024)

William Catterall, known as “the father of ion channels,” died on February 28 at the age of 77. Russ Hobbie and I cite Catterall’s article on the structure of sodium ion channels in Chapter 9 of Intermediate Physics for Medicine and Biology.

Payandeh J, Scheuer T, Zheng N, Catterall WA (2011) The crystal structure of a voltage-gated sodium channel. Nature 475:353–358.

Catterall worked in the intramural program at the National Institutes of Health in the laboratory of Marshall Nirenberg. He then moved to the University of Washington, where he was a professor of Pharmacology for over 40 years. There he was a collaborator with Bertil Hille, the author of the landmark textbook Ion Channels of Excitable Membranes. An obituary published by the University of Washington website states

First and foremost, Bill was an exceptional scientist. He pioneered the biochemical investigation of calcium and sodium ion channels; molecular portals that allow the controlled passage of ions across cell membranes. The proper passage of ions into the cell is essential for healthy brain, heart, and muscle function. Early work from Catterall elucidated the molecular basis of ion channel gating whereas later studies with UW Pharmacology colleague Dr. Ning Zheng revealed details of how these clinically relevant macromolecular machines operate at the atomic level. With this latter information, Catterall was able to ascertain how a variety of toxins as well as local anesthetics and antiarrhythmic drugs act to “lock the gate” on these ion channels. Bill was recognized for these pivotal discoveries by election to the National Academy of Sciences USA and the Royal Society London. He also received prestigious awards including the Gairdner Award from Canada, the Robert R. Ruffolo Career Achievement Award in Pharmacology from the American Society of Pharmacology and Therapeutics, and a Lifetime Achievement Award from the International Union of Pharmacologists.

To learn more, listen to Catterall discuss his work in a three-part series of lectures for iBiology. 

William Catterall (U. Washington) Part 1: Electrical Signaling: Life in the Fast Lane  

https://www.youtube.com/watch?v=QnQQkWxAKwI

 

William Catterall (U. Washington) Part 2: Voltage-gated Na+ Channels at Atomic Resolution

 https://www.youtube.com/watch?v=hfXGsJCOC9A

 

William Catterall (U. Washington) Part 3: Voltage-gated Calcium Channels

https://www.youtube.com/watch?v=bUE8gzMqqb8

Happy Birthday, Erwin Neher!

German biophysicist Erwin Neher turned 80 last week. Neher and Bert Sakmann received the 1991 Nobel Prize in Physiology or Medicine for their development of patch clamping: a method to record the current through individual ion channels. Russ Hobbie and I discuss Neher and Sakmann’s work in Chapter 9 of Intermediate Physics for Medicine and Biology.

I will turn over the rest of this post to Neher. In the two-minute video below, he offers advice to young scientists.

 

Erwin Neher's Advice to Young People: From a Nobel Prize Winner 

https://www.youtube.com/watch?v=vB3MNPuMFCI

 

In a ten-minute video, listen to Erwin Neher discuss advances in modern medicine.

Erwin Neher, Nobel Laureate for Medicine | Journal Interview 

https://www.youtube.com/watch?v=Rm3gHuxouZo

Finally, in this longer lecture, Neher describes the development of patch clamping. 

Lecture by Erwin Neher at the University of Hyderabad. The talk begins at approximately minute 18, after a rather long introduction.

https://www.youtube.com/watch?v=okB2coPEJJk

Happy Birthday, Erwin Neher!

A New Version of Figure 10.13 in the Sixth Edition of IPMB

Gene Surdotovich and I are hard at work preparing the 6^th edition of Intermediate Physics for Medicine and Biology. One change compared to the 5^th edition is that we are redrawing most of the figures using Mathematica. It’s a lot of work, but the revised figures look great and many are in color.

One advantage of redrawing the figures is that it forces us to rethink what the figure is all about and if it makes sense. This brings me to Figure 10.13 in the chapter about feedback. Specifically, it is from Section 10.6 about a negative feedback loop with two time constants. Without going into detail, let me outline what this figure is describing.

Chapter 10 centers around one particular feedback loop, relating the amount of carbon dioxide in your lungs (which we call x) to your breathing rate (y). The faster you breath, the more CO₂ you blow out of your lungs, so an increase in y causes a decrease in x. But your body detects when CO₂ is building up and reacts by increasing your breathing rate, so an increase in x causes an increase in y. There is one additional parameter, your metabolic rate, p. If your metabolic rate increases, so does the amount of CO₂ in your lungs.

Our book emphasizes mathematical modeling, so we develop a toy model of how x and y behave. We assume that initially x and y are in steady state for some p, and call these values x₀, y₀, and p₀. At time t = 0, p increases from  p₀ to p₀ + Δp, which could represent you starting to exercise. How do x and y change with time? We define two new variables, ξ and η, that represent the deviation of x and y from their steady state values, so x = x₀ + ξ and y = y₀ + η. We then develop two differential equations for ξ and η,

The variables ξ and η have different time constants, τ₁ and τ₂. The parameters G₁ and G₂ are the “gains” of the system, determining how much ξ changes in response to η, and how much η changes in response to ξ. In our model, G₁ is negative (an increase in breathing rate causes the amount of CO₂ in the lungs to decrease) and G₂ is positive (an increase in CO₂ causes the rate of breathing to increase). The “open loop gain” of the feedback loop is the product G₁G₂. Finally, the constant a is simply a factor to get the units right.

All is good so far. But now let’s look at the 5^th edition’s version of Fig. 10.13. 

What’s wrong with it? First, the calculation uses a positive value of G₁ and a negative value of G₂, so it doesn’t correspond correctly to our model, which has negative G₁ and positive G₂. Second, the calculation uses Δp = 0, so the steady state values of x and y don’t change and ξ and η both approach zero. That’s odd. I thought the whole point of the model was to look at how the system responds to changes in p. Finally, the initial values of ξ and η are not zero. What’s up with that? We know their values are zero for t < 0, when x = x₀ and y = y₀. How could they suddenly change at t = 0?

In the 6^th edition, the new version of Figure 10.13 is going to look something like this: 

The figure has color and switches from landscape to portrait orientation. Those changes are trivial. Here are the important differences:

1. I made G₁ negative and G₂ positive, like in our breathing model. Now an increase in CO₂ causes the body to increase the breathing rate, rather than decrease it as in the 5^th edition figure.
2. The parameter Δp is no longer zero. To be simple, I set aΔp = 1. The person starts exercising at t = 0.
3. Because there is a change in metabolic rate, the new steady state values of ξ and η are not zero. In fact, they are equal to ξ = aΔp/(1-G₁G₂) and η = G₂aΔp/(1-G₁G₂). Notice how the factor of 1-G₁G₂ plays a big role. Since the product G₁G₂ is negative, this means that 1-G₁G₂ is a positive number greater than one. It’s in the denominator, so it makes ξ smaller. That’s the whole point. The feedback loop is designed to keep ξ from changing much. It’s a control system to suppress changes in ξ. To make life simple, I set G₁ = −5 and G₂ = 5 (the same values from the 5^th edition except for the signs), so the open loop gain is 25 and the steady state value of ξ is only 1/26 of what it would be if no feedback were present (in which case, ξ would rise monotonically to one while η would remain zero).
4. The initial values of ξ and η are now zero, so there is no instantaneous jump of these variables at t = 0.

When revising the 5^th edition of IPMB, I began wondering why Russ Hobbie and I never worried about the units for the time constants, the gains, a, or Δp. This motivated me to write a new homework problem for the 6^th edition, in which the student is asked to rewrite the model equations in nondimensional variables Ξ, Η, and T instead of ξ, η, and t. Interestingly, such a switch results in a pair of differential equations for Ξ and Η that depend on only two nondimensional parameters: the ratio of time constants and the open loop gain. So, our plot in the 5^th edition has the qualitative behavior correct (except for the signs of G₁ and G₂). The system oscillates because the open loop gain is so high. The correct units for the various parameters would only rescale the horizontal and vertical axes. 

Is the new version of Figure 10.13 in this blog post what you’ll see in the 6^th edition of IPMB? I don’t know. I haven’t passed the figure by Gene yet, and he’s my Mathematica guru. He might make it even better.

What’s the moral of this story? THINK BEFORE YOU CALCULATE! That’s the motto I often would tell my students, but it applies just as well to textbook authors. The plot should not only be correct but also make physical sense. You should be able to explain what’s happening in words as well as pictures. If you can’t tell the story of what’s taking place by looking at the figure, something’s wrong.

Finally, is there really no physical problem that the original version of Fig. 10.13 describes? Actually, there is. Imagine you are resting throughout this “event”; you sit in your chair and don’t change your metabolic rate, so Δp = 0 meaning p is the same before and after t = 0. However, at time t = 0, your “friend” sneaks up on you, shoves a fire extinguisher in front of your face, and gives you a quick, powerful blast of CO₂. Except for the sign issue on G₁ and G₂, the original figure shows how your body would respond.

Stirling's Approximation

I've always been fascinated by Stirling’s approximation,

ln(n!) = n ln(n) − n,

where n! is the factorial. Russ Hobbie and I mention Stirling’s approximation in Appendix I of Intermediate Physics for Medicine and Biology. In the homework problems for that appendix (yes, IPMB does has homework problems in its appendices), a more accurate version of Stirling’s approximation is given as

ln(n!) = n ln(n) − n + ½ ln(2π n) .

There is one thing that’s always bothered me about Stirling’s approximation: it’s for the logarithm of the factorial, not the factorial itself. So today, I’ll derive an approximation for the factorial. 

The first step is easy; just apply the exponential function to the entire expression. Because the exponential is the inverse of the natural logarithm, you get

n! = e^{n ln(n) − n + ½ ln(2π n)}

Now, we just use some properties of exponents

n! = e^{n ln(n)} e⁻ⁿ e^{½ln(2π n)}

n! = (e^ln(n))ⁿ e⁻ⁿ √(e^{ln(2π n)})

n! = nⁿ e⁻ⁿ √(2π n) 

And there we have it. It’s a strange formula, with a really huge factor (nⁿ) multiplied by a tiny factor (e⁻ⁿ) times a plain old modestly sized factor (√(2π n)). It contains both e = 2.7183 and π = 3.1416.

Let's see how it works.

n	n!	nn e−n √(2π n)	fractional error (%)
1	1	0.92214	7.8
2	2	1.9190	4.1
5	120	118.02	1.7
10	3.6288 × 106	3.5987 × 106	0.83
20	2.4329 × 1018	2.4228 × 1018	0.42
50	3.0414 × 1064	3.0363 × 1064	0.17
100	9.3326 × 10157	9.3249 × 10157	0.083

For the last entry (n = 100), my calculator couldn’t calculate 100¹⁰⁰ or 100!. To get the first one I wrote

100¹⁰⁰ = (10²)¹⁰⁰ = 10^{2 × 100} = 10²⁰⁰.

The calculator was able to compute e⁻¹⁰⁰ = 3.7201 × 10⁻⁴⁴, and of course the square root of 200π was not a problem. To obtain the actual value of 100!, I just asked Google.

Why in the world does anyone need a way to calculate such big factorials? Russ and I use them in Chapter 3 about statistical dynamics. There you have to count the number of states, which often requires using factorials. The beauty of statistical mechanics is that you usually apply it to macroscopic systems with a large number of particles. And by large, I mean something like Avogadro’s number of particles (6 × 10²³). The interesting thing is that in statistical mechanics you often need not the factorial, but the logarithm of the factorial, so Stirling's approximation is exactly what you want. But it’s good to know that you can also approximate the factorial itself. 

Finally, one last fact from Mr. Google. 1,000,000! = 8.2639 × 10^5,565,708. Wow!

Stirling’s Approximation

https://www.youtube.com/watch?v=IJ5N28-Ujno

A Text-Book on Medical Physics

Intermediate Physics for Medicine and Biology provides, for the first time, a textbook about the role that physics plays in medicine.

Well… no.

I recently found a textbook that preceded IPMB by over a century. Below is its preface.

The fact that a knowledge of Physics is indispensable to a thorough understanding of Medicine has not yet been as fully realized in this country as in Europe, where the admirable works of Desplats and Gariel, of Robertson, and of numerous German writers, constitute a branch of educational literature to which we can show no parallel. A full appreciation of this, the author trusts, will be sufficient justification for placing in book form the substance of his lectures on this department of science, delivered during many years at the University of the City of New York.

Broadly speaking, this work aims to impart a knowledge of the relations existing between Physics and Medicine in their latest state of development, and to embody in the pursuit of this object whatever experience the author has gained during a long period of teaching this special branch of applied science. In certain cases topics not strictly embraced in the title have been included in the text—for example, the directions for section-cutting and staining; and in other instances exceptionally full descriptions of apparatus have been given, notably of the microscope; but in view of the importance of these subjects, the course pursued will doubtless be approved. Attention may be called to the paragraph headings and italicized words, which suggest a system of questions facilitating a review of the text.

In conclusion, the author will feel that his labor has not been in vain if the work should serve to call deserved attention to a subject hitherto slighted in the curriculum of medical education.

Readers of IPMB might be interested in a brief table of contents for this earlier book.

I. Matter

      1. Properties of matter

      2. Solid matter

      3. Liquid matter

      4. Gaseous matter

      5. Ultragaseous and radiant matter

II. Energy

               1. Potential energy 

               2. Kinetic energy 

               3. Machines and instruments 

               4. Translatory molecular motion 

               5. Acoustics 

               6. Optics 

               7. Heat 

               8. Electricity 

               9. Dynamic electricity 

             10. Magnetism 

             11. Electrobiology

Many of these topics are familiar to readers of IPMB. Yet, the list and the language seem quaint and just a little old-fashioned.

A Text-Book on Medical Physics,
by John C. Draper.

This should not be surprising. The book was titled A Text-Book on Medical Physics, written by John C. Draper, and published in 1885. Russ Hobbie and I are following a long tradition of applying physics to medicine and biology. In nearly 140 years much has changed, but also much has stayed the same. The last sentence of the preface could serve as our call to arms, and the subtitle of Draper’s book could be our own: “For the Use of Students and Practitioners of Medicine.” 

Below I post the definition of medical physics in the Text-Book. I love it. Draper should have written a blog!